- MyIllumina
- Tools
Broadening our Understanding of Gene Regulation
Not all changes in the regulation of gene expression are caused by variation in the underlying DNA sequence. Epigenetics is the study of gene regulation through other mechanisms, including DNA methylation, small RNA-mediated regulation, and alterations in DNA / protein interactions such as those affecting chromatin structure and transcription factor binding. Illumina has a broad portfolio of epigenetics analysis tools, and works with leading experts to ensure that it meets the field’s rapidly evolving needs and provides solutions that are easily accessible to investigators interested in adding epigenetic applications to their study designs.
- ARRAY-BASED METHYLATION ANALYSIS
- SEQ-BASED METHYLATION ANALYSIS
- SMALL RNA ANALYSIS
- CHIP-SEQ
- LOW TO MID-PLEXITY OPTIONS
Description
Array-Based Methylation Analysis
With Infinium Methylation Assays, researchers can quantitatively interrogate methylation sites at single-nucleotide resolution, profiling 12 samples in parallel to deliver high-throughput power while minimizing the cost per sample. The HumanMethylation27 BeadChip enables economical analysis of 27,578 CpG loci, covering more than 14,000 genes with enhanced coverage of cancer-related content. The HumanMethylation450 BeadChip offers a unique combination of comprehensive, expert-selected coverage, including 99% of RefSeq genes, 96% of CpG islands, and other content categories selected by methylation experts, delivering high throughput at a low price, making it ideal for epigenome-wide association studies (EWAS).
Documentation
FAQs
Software |
|---|
|
Infinium Methylation Data Analysis The analysis of Infinium methylation data is performed using the GenomeStudio Methylation Module. This program enables two basic types of methylation data analysis: calculating methylation levels within an individual sample; and determining whether methylation levels have changed between a reference group and another experimental group. The GenomeStudio Methylation Module workflow is shown in the diagram below. Note that additional, third party analysis tools complimentary to the GenomeStudio Methylation Module are also available. Learn more about the Illumina GenomeStudio methylation module.   GenomeStudio supports DNA methylation analysis on any platform. Data are displayed in intuitive graphics. Gene expression data can be integrated easily with methylation projects (plotted on right).
|
Kits
Key Publications |
|---|
| Infinium HumanMethylation27 BeadChip Li L, Lee KM, Han W, Choi JY, Lee JY, et al. (2010) Estrogen and progesterone receptor status affect genome-wide DNA methylation profile in breast cancer. Hum Mol Genet 19:4273-4277. Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 17:510-522. Hinoue T, Weisenberger DJ, Lange CP, Shen H, Byun HM, et al. (2011) Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Genome Res June 9 Epub ahead of print. Thirlwell C, Eymard M, Feber A, Teschendorff A, Pearce K, et al. (2010) Genome-wide DNA methylation analysis of archival formalin-fixed paraffin-embedded tissue using the Illumina Infinium HumanMethylation27 BeadChip. Methods 52:248-254. Infinium HumanMethylation450 BeadChipSandoval J, Heyn HA, Moran S, Serra-Musach J, Pujana MA, et al. (2011) Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 6:692-702. Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, et al. (2011) High density DNA methylation array with single CpG site resolution. Genomics 8: Epub ahead of print. ReviewsRakyan VK, Down TA, Balding DJ, Beck S. (2011) Epigenome-wide association studies for common human diseases. Nat Rev Genet. 12:529-541. Infinium Methylation Data AnalysisMancuso FM, Montfort M, Carreras A, Alibés A, and Roma G. (2011) HumMeth27QCReport: an R package for quality control and primary analysis of Illumina Infinium methylation data. BMC Res Notes 4:546. Wang D, Yan L, Hu Q, Sucheston LE, Higgins MJ, et al. (2012) IMA: an R package for high-throughput analysis of Illumina 450K Infinium methylation data. Bioinformatics 5:729-730. Kilaru V, Barfield RT, Schroeder JW, Smith AK, and Conneely KN. (2012) MethLAB: a graphical user interface package for the analysis of array-based DNA methylation data. Epigenetics 7:225-229. Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, and Fuks F. (2011) Evaluation of the Infinium Methylation 450K technology. Epigenomics 3:771-84. View a complete, searchable list of Illumina publications. |
Description
Sequencing-Based Methylation Analysis
Sequencing-based DNA methylation analysis applies the coverage density and flexibility enabled by next-generation sequencing to enhance epigenetic studies. A number of different approaches have been established, each offering unique advantages suitable for different types of study designs (see References). Among the materials listed below are protocols, reagent information, and data analysis software supporting two forms of bisulfite sequencing-based applications: whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS). Publication references supporting other approaches are included as well.
Documentation
- Whole‐Genome Bisulfite Sequencing for Methylation Analysis Guide
- Reduced Representation Bisulfite Sequencing for Methylation Analysis Guide
FAQs
Software |
|---|
|
WGBS and RRBS Sequencing Analysis The methylation data analysis pipeline consists of three principle steps: adaptor trimming, alignment, and base-by-base methylation calling. Additional features may include SAM file output, generation of tracks for viewing in IGV and UCSC genome browser, and summary statistics. Available tools for analysis include Bismark, BSMap/RRBSMap, BS Seeker, MethylCoder, RMAP (SE only).    |
Kits
Whole-Genome Bisulfite Sequencing
Sample Preparation Kits
- Paired-end DNA Sample Prep Kit (Please refer to the WGBS for Methylation Analysis Guide for information regarding required adaptors and other consumables)
SBS / Cluster Kits
A full list of kits compatible with your instrument may be found on the Systems page. For WGBS, Illumina recommends using paired-end reads of at least 75 bp.
Reduced Representation Bisulfite Sequencing
Sample prep kits
- Paired-end DNA Sample Prep Kit (Please refer to the RRBS for Methylation Analysis Guide for information regarding required adaptors and other consumables)
SBS / Cluster kits
A full list of kits compatible with your instrument may be found on the Systems page. For RRBS, Illumina recommends using single reads of at least 50 bp.
Key Publications |
|---|
| WGBS Lister R, Pelizzola M, Kida YS, Hawkins RD, Nerv JR, et al. (2011) Hotspots of aberrant epigenomics reprogramming in human induced pluripotent stem cells. Nature 471:66-73. Li Y, Zhu J, Tian G, Li N, Li Q, et al. (2010) The DNA methylome of human peripheral blood mononuclear cells. PLoS Biol 8:e100053. Laurent L, Wong E, Li G, Huynh T, Tsirigos A, et al. (2010) Dynamic changes in the human methylome during differentiation. Genome Res 20:320-321. Feng S, Cokus SJ, Zhang X, Chen PY, Bostick M, et al. (2010) Conservation and divergence of methylation patterning in plants and animals. Proc Natl Acad Sci USA 107:8689-8694. RRBSGu H, Smith ZD, Bock C, Boyle P, Gnirke A, et al. (2011) Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat Protoc 6:468-481. Gertz J, Varley KE, Reddy TE, Bowling KM, Pauli F, et al. (2011) Analysis of DNA methylation in a three-generation family reveals widespread genetic influence on epigenetic regulation. PLoS Genet. 7:e10022228. Other ApplicationsPomraning KR, Smith KM, Freitag M. (2009) Genome-wide high throughput analysis of DNA methylation in eukaryotes. Methods 47:142-150. Serre D, Lee BH, Ting AH. (2010) MBD-isolated genome sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome. Nucleic Acids Res 38:391-399. Brinkman AB, Simmer F, Ma K, Kaan A, Zhu J, et al. (2010) Whole-genome DNA methylation using MethylCap-seq. Methods 52:232-236. ReviewsBock C, Tomazou EM, Brinkman AB, Müller F, Simmer F, et al. (2010) Quantitative comparison of genome-wide DNA methylation mapping technologies. Nat Biotechnol 28:1106-1114. Laird P. (2010) Principles and challenges of genome-wide DNA methylation analysis. Nat Rev Genet 11:191-203. View a complete, searchable list of Illumina publications. |
Description
Small RNA Analysis
Small RNA sequencing is a powerful application for Illumina Sequencing, enabling the discovery and profiling of microRNAs and other non-coding RNA on any organism, without prior genome annotation. Using low RNA inputs, you can profile the differential expression of known microRNAs, as well as detect novel microRNA targets and wide-ranging sequence variation or "iso-miRs" miRBase accessions. With unprecedented sensitivity and dynamic range, Illumina's industry-leading small RNA sequencing methods enable the most accurate detection and quantification of rare small RNA sequences.
Documentation
- TruSeq Small RNA Sample Preparation Guide
- TruSeq Small RNA Sample Preparation Experienced User Card
- TruSeq Small RNA Sample Preparation Lab Tracking Form
- HiSeq Systems Specification Sheet
- Genome Analyzer IIx Data Sheet
- HiScanSQ Specification Sheet
- Small RNA Sample Prep Product Guide v1.5
FAQs
Software |
|---|
|
Small RNA Data Analysis The small RNA data analysis pipeline consists of end trimming, alignment against “contamination” files (i.e. mitochondrial DNA, rRNA, primers, etc.), and then alignment of filtered reads against the full genome, and optionally, miRbase for both miRNA and miRNA loop sequences. Additionally, third party analysis tools are also available and include (but are not limited to) miRTools, miRDeep, deepBase, miRExpress, miRAnalyzer , CID-miRNA and miR-Cat. Illumina’s small RNA data analysis solution, Flicker 3.0, covers each of the steps described in the flow diagram. The figure below shows distinct miRNA expression profiles visualized using both a heatmap (left) and pair-wise comparison (right) as generated using Flicker 3.0. Learn more and download Flicker 3.0 software.   Comparison of five body map microRNA samples using heatmap. (left)
Pair-wise comparison of brain and heart microRNA samples. (right) |
Kits
Sample Preparation Kits
SBS / Cluster Kits
A full list of kits compatible with your instrument may be found on the Systems page. For small RNA analysis, Illumina recommends using single reads of at least 35 bp.
Description
ChIP-Seq
By combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing, ChIP-Seq can be used to accurately survey interactions between protein, DNA, and RNA, enabling the interpretation of regulation events central to many biological processes and disease states. Leveraging Illumina’s industry-leading sequencing technology, ChIP-Seq can identify a broad range of protein/nucleic acid interactions with confidence, generating millions of counts across multiple, indexed samples per lane for cost-effective and precise analysis.
Documentation
FAQs
Software |
|---|
|
ChIP-Seq Data Analysis The Illumina ChIP Sequencing Module analyzes data from Illumina Whole-Genome Chromatin Immunoprecipitation Sequencing (ChIP-Seq) experiments. ChIP-Seq combines ChIP assays with massively parallel DNA sequencing using the Illumina GenomeAnalyzer. This enables cost-effective and precise mapping of global binding sites for DNA-associated proteins. The ChIP Sequencing Module enables two types of data analysis: peak or region finding (identifying the binding sites for DNA-associated proteins); and differential analysis (determining whether binding levels have changed between two experimental groups). You can zoom in on regions with interesting binding patterns, compare sample-to-sample or sample-to-control, and export data for secondary analysis. Learn more about the Illumina ChIP sequencing data analysis solution.   View of ChIP-Seq peaks at single site across multiple samples.
Chromosome view of ChIP-Seq peaks with gene information.
|
Kits
Sample Preparation Kits
SBS / Cluster Kits
A full list of kits compatible with your instrument may be found on the Systems page. For ChIP-Seq, Illumina recommends using single reads of at least 50 bp.
Key Publications |
|---|
|
Drost J, Mantovani F, Tocco F, Elkon R, Comel A, et al. (2010) BRD7 is a candidate tumour suppressor gene required for p53 function. Nat Cell Biol 12:380-389. Thomson JP, Skene PJ, Selfridge J, Clouaire T, Guy J, et al. (2010) CpG islands influence chromatin structure via the CpG-binding protein Cfp1. Nature 464:1082-1086. Yan Z, Hu HY, Jiang X, Maierhofer V, Neb E, et al. (2011) Widespread expression of piRNA-like molecules in somatic tissues. Nucleic Acids Res 39:6596-6607. Vermeulen M, Eberl HC, Matarese F, Marks H, Denissov S, et al. (2010) Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers. Cell 142:967-980. View a complete, searchable list of Illumina publications. |
Description
Low- to Mid-Plex Custom Methylation
For methylation profiling studies requiring low- to mid-plex analysis, Illumina provides customized solutions that allow researchers to target CpG loci within genes or regions of interest.
GoldenGate Customized Methylation Panels on VeraCode
Methylation profiling with Veracode technology provides a simplified workflow, high-throughput sample processing, and assay flexibility. A customized panel of 96-384 CpG regions can be profiled simultaneously, and hundreds of samples can be read per day with the BeadXpress Reader. Individual bead types can be combined in unlimited combinations to support flexible assay design tailored to specific applications. Submit your desired list of CpG regions, and Illumina scientists will help you create successful custom content for multiplexed GoldenGate Methylation assays.
Methylation-Specific qPCR
Real-Time PCR enables the amplification, detection, and precise quantification of target DNA sequences by measuring the fluorescent signal at each cycle of PCR and during amplicon dissociation. Several new applications have been developed that utilize Real-Time PCR technology for both qualitative and quantitative analysis of DNA methylation. One approach involves bisulfite conversion followed by Methylation Specific PCR (MSP) to specifically amplify methylated or unmethylated targets, while the other leverages Methylation-Sensitive High Resolution Melting (MS-HRM) to determine the percent methylation of a particular target down to as low as 1% within a pool of sample DNA. The Eco Real-Time PCR System puts these powerful qPCR applications within reach of individual researchers.
Documentation
Eco Real-Time PCR System
GoldenGate VeraCode
- Designing Custom GoldenGate Methylation Profiling Panels
- High-Throughput DNA Methylation Profiling with VeraCode Technology
Software |
|---|
|
GoldenGate Methylation on VeraCode Data Analysis Like all Illumina products, methylation assay results are collected and analyzed by the powerful Illumina GenomeStudio analysis software. GenomeStudio features an intuitive graphic interface for easy interpretation of results. The Genome-Studio Methylation Module offers an integrated set of powerful analysis tools for characterizing, measuring, and visualizing methylation profiling results. Illumina’s methylation assay technology and design are consistent with other Illumina applications, including gene expression profiling. This enables researchers to perform cross-application analysis such as integrating gene expression data with DNA methylation data in GenomeStudio.   Methylation status (beta value) is shown for may loci (y-axis) across many samples (y-axis) in graphical heat map format to reveal trends and outliers.
Control summary graph from GenomeStudio.
Eco Real-Time PCR Methylation-Specific PCR Data Analysis Several applications have been developed that utilize Real-Time PCR technology for both qualitative and quantitative analysis of DNA methylation. These methods involve bisulfite conversion followed by either Methylation Specific PCR (MSP) to specifically amplify methylated or unmethylated targets or Methylation-Sensitive High Resolution Melting (MS-HRM). The Eco Real-Time PCR System has industry leading thermal uniformity among block-based Real-Time PCR instruments, facilitating the detection of as little as 1% methylated target within a pool of sample DNA. Learn more about methylation analysis on the Eco System.  Standard curve demonstrating detection of 1% methylation within a region of the ESR1 promoter. |
Systems and Kits
Eco Real-Time PCR System
Goldengate Veracode
Technology Overviews
View more Eco Training Modules.
At Illumina, our goal is to apply innovative technologies and revolutionary assays to the analysis of genetic variation and function, making studies possible that were not even imaginable just a few years ago. These studies will help make the realization of personalized medicine possible. With such rapid advances in technology taking place, it is mission critical to have solutions that are not only innovative, but flexible, scalable, and complete with industry-leading support and service. As a global company that places high value on collaborative interactions, rapid delivery of solutions, and prioritizing the needs of its customers, we strive to meet this challenge. Illumina's innovative, array-based solutions for DNA, RNA, and protein analysis serve as tools for disease research, drug development, and the development of molecular tests in the clinic.